
"""simple docstring"""



import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin




@skip_mps
class 		a_    (			__lowerCAmelCase  ,    __lowerCAmelCase  ,    unittest.TestCase						):
    a   :					Union[str, Any]			     =					IFInpaintingPipeline
    a   :					str			     =					TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'width', 'height'}
    a   :					List[str]			     =					TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
    a   :					List[str]			     =					PipelineTesterMixin.required_optional_params - {'latents'}







    def   _snake_case       (      self      :							Union[str, Any]  )		->Any:






        '''simple docstring'''






        return self._get_dummy_components()







    def   _snake_case       (      self      :							Optional[Any]  ,       __UpperCamelCase      :							Optional[Any]  ,       __UpperCamelCase      :							Tuple=0  )		->Any:






        '''simple docstring'''






        if str(lowerCamelCase_  ).startswith("""mps"""  ):
            _UpperCAmelCase        = torch.manual_seed(lowerCamelCase_  )
        else:
            _UpperCAmelCase        = torch.Generator(device=lowerCamelCase_  ).manual_seed(lowerCamelCase_  )

        _UpperCAmelCase        = floats_tensor((1, 3, 32, 32)  ,       rng=random.Random(lowerCamelCase_  )  ).to(lowerCamelCase_  )
        _UpperCAmelCase        = floats_tensor((1, 3, 32, 32)  ,       rng=random.Random(lowerCamelCase_  )  ).to(lowerCamelCase_  )

        _UpperCAmelCase        = {
            """prompt""": """A painting of a squirrel eating a burger""",
            """image""": image,
            """mask_image""": mask_image,
            """generator""": generator,
            """num_inference_steps""": 2,
            """output_type""": """numpy""",
        }

        return inputs







    @unittest.skipIf(
        torch_device != """cuda""" or not is_xformers_available()  ,       reason="""XFormers attention is only available with CUDA and `xformers` installed"""  ,       )
    def   _snake_case       (      self      :							Optional[int]  )		->Optional[int]:






        '''simple docstring'''






        self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3  )







    def   _snake_case       (      self      :							Tuple  )		->Dict:






        '''simple docstring'''






        self._test_save_load_optional_components()







    @unittest.skipIf(torch_device != """cuda"""  ,       reason="""float16 requires CUDA"""  )
    def   _snake_case       (      self      :							str  )		->int:






        '''simple docstring'''






        super().test_save_load_floataa(expected_max_diff=1e-1  )







    def   _snake_case       (      self      :							List[str]  )		->Any:






        '''simple docstring'''






        self._test_attention_slicing_forward_pass(expected_max_diff=1e-2  )







    def   _snake_case       (      self      :							str  )		->List[str]:






        '''simple docstring'''






        self._test_save_load_local()







    def   _snake_case       (      self      :							Union[str, Any]  )		->Optional[int]:






        '''simple docstring'''






        self._test_inference_batch_single_identical(
            expected_max_diff=1e-2  ,       )
def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	List[str]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )
 if n == 0:
  return 0
 UpperCamelCase			  =      float("""-inf"""       )
 for i in range(1							,					n + 1       ):
  UpperCamelCase			  =      max(
      UpperCamelCase_							,					prices[i - 1] + naive_cut_rod_recursive(n - i							,					UpperCamelCase_       )       )

 return max_revue





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Optional[Any]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      [float("""-inf"""       ) for _ in range(n + 1       )]
 return _top_down_cut_rod_recursive(UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_							,					UpperCamelCase_       )		->	List[Any]:







 '''simple docstring'''
 if max_rev[n] >= 0:
  return max_rev[n]
 elif n == 0:
  return 0
 else:
  UpperCamelCase			  =      float("""-inf"""       )
  for i in range(1							,					n + 1       ):
   UpperCamelCase			  =      max(
       UpperCamelCase_							,					prices[i - 1] + _top_down_cut_rod_recursive(n - i							,					UpperCamelCase_							,					UpperCamelCase_       )							,					)

  UpperCamelCase			  =      max_revenue

 return max_rev[n]





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Union[str, Any]:







 '''simple docstring'''
 _enforce_args(UpperCamelCase_							,					UpperCamelCase_       )

 # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
 # length 0.
 UpperCamelCase			  =      [float("""-inf"""       ) for _ in range(n + 1       )]
 UpperCamelCase			  =      0

 for i in range(1							,					n + 1       ):
  UpperCamelCase			  =      max_rev[i]
  for j in range(1							,					i + 1       ):
   UpperCamelCase			  =      max(UpperCamelCase_							,					prices[j - 1] + max_rev[i - j]       )

  UpperCamelCase			  =      max_revenue_i

 return max_rev[n]





def 			lowercase(	UpperCamelCase_							,					UpperCamelCase_       )		->	Union[str, Any]:







 '''simple docstring'''
 if n < 0:
  UpperCamelCase			  =      f"""n must be greater than or equal to 0. Got n = {n}"""
  raise ValueError(UpperCamelCase_       )

 if n > len(UpperCamelCase_       ):
  UpperCamelCase			  =      (
      """Each integral piece of rod must have a corresponding price. """
      f"""Got n = {n} but length of prices = {len(UpperCamelCase_       )}"""
  )
  raise ValueError(UpperCamelCase_       )





def 			lowercase(	)		->	str:







 '''simple docstring'''
 UpperCamelCase			  =      [6, 10, 12, 15, 20, 23]
 UpperCamelCase			  =      len(UpperCamelCase_       )

 # the best revenue comes from cutting the rod into 6 pieces, each
 # of length 1 resulting in a revenue of 6 * 6 = 36.
 UpperCamelCase			  =      36

 UpperCamelCase			  =      top_down_cut_rod(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      bottom_up_cut_rod(UpperCamelCase_							,					UpperCamelCase_       )
 UpperCamelCase			  =      naive_cut_rod_recursive(UpperCamelCase_							,					UpperCamelCase_       )

 assert expected_max_revenue == max_rev_top_down
 assert max_rev_top_down == max_rev_bottom_up
 assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
     main()
